A CMOS imager circuit includes a focal plane array of pixel cells, each one of the cells including a photosensor, for example, a photogate, photoconductor or a photodiode overlying a substrate for accumulating photo-generated charge in the underlying portion of the substrate. Each pixel cell has a readout circuit that includes at least an output field effect transistor formed in the substrate and a charge storage region formed on the substrate connected to the gate of an output transistor. The charge storage region may be constructed as a floating diffusion region. Each pixel may include at least one electronic device such as a transistor for transferring charge from the photosensor to the storage region and one device, also typically a transistor, for resetting the storage region to a predetermined charge level prior to charge transference.
In a CMOS imager, the active elements of a pixel cell perform the necessary functions of: (1) photon to charge conversion; (2) accumulation of image charge; (3) resetting the storage region to a known state before the transfer of charge to it; (4) transfer of charge to the storage region accompanied by charge amplification; (5) selection of a pixel for readout; and (6) output and amplification of a signal representing pixel charge. Photo charge may be amplified when it moves from the initial charge accumulation region to the storage region. The charge at the storage region is typically converted to a pixel output voltage by a source follower output transistor.
CMOS imagers of the type discussed above are generally known as discussed, for example, in U.S. Pat. No. 6,140,630, U.S. Pat. No. 6,376,868, U.S. Pat. No. 6,310,366, U.S. Pat. No. 6,326,652, U.S. Pat. No. 6,204,524 and U.S. Pat. No. 6,333,205, assigned to Micron Technology, Inc., which are hereby incorporated by reference in their entirety.
A typical four transistor (4T) CMOS imager pixel 10 is shown in FIG. 1. The pixel 10 includes a photosensor 12 (e.g., photodiode, photogate, etc.), transfer transistor 14, floating diffusion region FD, reset transistor 16, source follower transistor 18 and row select transistor 20. The photosensor 12 is connected to the floating diffusion region FD by the transfer transistor 14 when the transfer transistor 14 is activated by a transfer gate control signal TX.
The reset transistor 16 is connected between the floating diffusion region FD and an array pixel supply voltage Vaa_pix. A reset control signal RST is used to activate the reset transistor 16, which resets the floating diffusion region FD to the array pixel supply voltage Vaa_pix level as is known in the art.
The source follower transistor 18 has its gate connected to the floating diffusion region FD and is connected between the array pixel supply voltage Vaa_pix and the row select transistor 20. The source follower transistor 18 converts the charge stored at the floating diffusion region FD into an electrical output voltage signal Vout. The row select transistor 20 is controllable by a row select signal SEL for selectively connecting the source follower transistor 18 and its output voltage signal Vout to a column line 22 of a pixel array.
There are a variety of applications that benefit from the ability to sense scene information in the pixel array prior to readout. These applications include e.g., motion estimation to compensate for camera movement (hand jitter), object motion tracking to assist with compressing video streams, auto-exposure, and auto-white balancing. With the ability to track camera movement, digital imager control circuits can adjust the starting position of a readout operation (typically, the array contains additional row and columns to allow a smaller window to be readout to keep the image centered in the frame for electronic stabilization).
Estimating localized motion of objects in the array prior to image readout also allows for video stream compression. This occurs by reading out only the portion of the image that has changed relative to the prior image frame. For long exposures used in the capture of still images, motion blur can be eliminated if the motion is sensed during integration and sub-frames are discarded while good frame data is being accumulated in the pixel. The motion estimation approach that enables the above functions also allows the detection of the magnitude of signals in the scene, which can be used to predict proper exposure and light temperatures (for a sensor with color filters).
The statistics gathered prior to image readout can be used to adjust the window start location, window size, integration time, and signal gain. The statistics can also be used with digital image processing algorithms to assist image processing functions like motion detection, auto-exposure, and auto-white balancing. Other techniques to perform these operations include: (1) using frame memories and digital image processing to track motion; or (2) incorporating separate motion detectors in the camera (e.g., gyros) to detect camera motion. These techniques, however, are undesirable.
Accordingly, there is a need and desire for a scene sensing technique that gathers image scene statistics usable to e.g., detect motion or process signals faster than prior art techniques and without the need for additional memory or discrete external components.